Process images with vision API

vision.py

def image_to_object_localization(
        project_id, sub_name, duration, binary, cloud_region, registry_id,
        device_id):
    import base64
    import binascii
    import io
    import time

    from google.cloud import pubsub
    from google.cloud import vision

    from PIL import Image, ImageDraw, ImageFont

    subscriber = pubsub.SubscriberClient()
    subscription_path = subscriber.subscription_path(project_id, sub_name)

    global count
    count = 0


    def callback(message):
        global count
        try:
            count = count + 1
            print('Received image {}:'.format(count))
            image_data = message.data
            if not binary:
                image_data = base64.b64decode(image_data)

            client = vision.ImageAnnotatorClient()

            image = vision.types.Image(content=image_data)

            objects = client.object_localization(
                image=image).localized_object_annotations

            filename = 'vision.jpg'
            with io.open(filename, 'wb') as f:
                f.write(image_data)

            print('Number of objects found: {}'.format(len(objects)))
            label_csv = ''

            for object_ in objects:
                print('\n{} (confidence: {})'.format(
                    object_.name, object_.score))

            with Image.open(filename) as img:
                img.show()

            message.ack()